AI-Driven Secure Software Development Lifecycle (SDLC)
DOI:
https://doi.org/10.15662/IJARCST.2025.0801003Keywords:
Artificial Intelligence, Software Security, Vulnerability Detection, Secure Coding, Threat Mitigation, Real-Time Detection, SDLC Phases, Process AutomationAbstract
Introduction of Artificial Intelligence (AI) in the Software Development Lifecycle (SDLC) is a dramatic change in the control of software security. This study explores the potential of AI in helping to supplement the conventional SDLC activities, including vulnerability detection in an automated fashion, secure coding habits, and assessing the threat in real-time. This paper examines how AI aids in detecting security vulnerabilities throughout the pre-development phase, helping developers create more robust code and automatically identify and react to security threats within the software execution environment. With a mixed-method design, this study synthesizes case studies and practical data to determine the effectiveness of AI in various SDLC stages. The main conclusions are that AI-based solutions maximize the detection of vulnerabilities, increase the code quality, and minimize the time spent responding to security threats. The study reveals that AI integration not only enhances software security but also promotes SDLC efficiency, providing a scalable and dependable solution to the changing cybersecurity issues.
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